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A Discriminative Image Registration Model with Hybrid Feature Detector

Author

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  • Syed Abdul Hanan Ahmed Shah
  • Shahnawaz Talpur
  • Bushra Naz

Abstract

Image registration is a manner of aligning two or more images of the same scene which achieves maximum accuracy. Analysis of geometric distortion, caused by the difference in viewing angle, sensor resolution and distance. The critical step in image registration is the collection of feature points and evaluate a spatial transformation mainly when outliers are present. In our proposed framework we have used the hybrid feature-based and area-based methods together. Before applying those methods, the Bilateral Filter is applied for the preprocessing of both the images, the reference image and the image that needs to be registered in order to make the images noise free. For feature detection, the ORB (Oriented FAST and Rotated BRIEF) is used which is basically a fusion of FAST key point detector and BRIEF descriptor with many modifications to enhance the performance. KNN (K-Nearest Neighbors) is used for matching similar points and for reducing the miss matches the efficient algorithm is used which is Random Sample Consensus (RANSAC). The template matching method is applied for the area-based matching.

Suggested Citation

  • Syed Abdul Hanan Ahmed Shah & Shahnawaz Talpur & Bushra Naz, 2023. "A Discriminative Image Registration Model with Hybrid Feature Detector," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 9(3), pages 272-278, June.
    • Handle: RePEc:jbh:ijsrcs:v9:y2023:i3:id:hcseit2390369
    DOI: 10.32628/CSEIT2390369
    Note: Article URL: https://ijsrcseit.com/CSEIT2390369
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